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Accelerated Genetic Programming for Intelligent Fuzzy Robots
Yasuyuki Murai*, Koki Matsumura**, Hisayuki Tatsumi***, Hiroyuki Tsuji*, and Shinji Tokumasu*
*Department of Information and Computer Sciences, Kanagawa Institute of Technology, 1030 Shimoogino, Atsugi, Kanagawa 243-0292, Japan
**Department of Information and Knowledge Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Tottori 680-8550, Japan
***Department of Computer Science, Tsukuba College of Technology, 4-12-7 Kasuga, Tsukuba, Ibaraki 305-0821, Japan
Received:July 22, 2004Accepted:September 12, 2004Published:November 20, 2004
Keywords:fuzzy, robot, genetic programming, coupled chaotic system,
Abstract
We previously proposed a new way of automatically generating membership functions that play an important role in improving the accuracy of fuzzy control by using genetic programming (GP). In this paper, we report 2 improvements for achieving better fuzzy robot intelligence. First, we made the mutation rate change dynamically based on a coupled chaotic system. Secondly, we introduced population partitioning using deme by parallel processing. The effectiveness of these improvements is demonstrated through computer simulation.
Cite this article as:Y. Murai, K. Matsumura, H. Tatsumi, H. Tsuji, and S. Tokumasu, “Accelerated Genetic Programming for Intelligent Fuzzy Robots,” J. Adv. Comput. Intell. Intell. Inform., Vol.8 No.6, pp. 582-590, 2004.Data files:
